A system and method for efficiently processing and managing data stored in a queue. A processing device may process the data stored in the queue. Queue protocols can be applied to the queue to efficiently process and manage data stored in the queue. Queue protocols may facilitate efficient use of processing resources that process the data stored in one or more queues. A queue protocol may include at least a first protocol for facilitating transfer of data in the queue to another queue processed by another processing device or a second protocol for inhibiting transfer of data in the queue to another queue.
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1. A system for predicting total allocation of resources in an event, the system comprising: one or more processors; and a non-transitory computer-readable storage medium storing instructions configured to execute on the one or more processors, causing the one or more processors to perform operations including: accessing one or more data sources storing a plurality of access rights to a resource, wherein each of the access rights is associated with an attribute; generating load data representing a load of user requests, wherein the load of the user requests including requests received from a plurality of user devices requesting that an access right to the resource be allocated to the user device; generating a queue of the user requests based on the load of the user requests received, wherein the queue is generated of users interested in attending the event; predicting probability of allocation of access rights of each of the user requests; identifying current value of the resource associated with the access rights; estimating total value of the resources based on the load of user requests in the queue and the current value of the resources, wherein the total value of resources is sum of all the resources associated each of the access rights; and adjusting the value of the resources if the total estimated value of the resources is greater than or less than a threshold.
The system predicts the total allocation of resources for an event by analyzing access rights and user demand. The system operates in domains such as event management, ticketing, or resource allocation where predicting demand and optimizing resource distribution is critical. The problem addressed is the need to accurately forecast resource allocation to maximize value while preventing over- or under-allocation. The system accesses data sources containing access rights to a resource, where each right has associated attributes. It generates load data representing user request volume, including requests from multiple devices seeking resource allocation. A queue of these requests is formed, representing users interested in attending an event. The system predicts the probability of allocating access rights to each request and identifies the current value of the resources. It then estimates the total value of resources by summing the values of all access rights, based on the queue and current values. If the total estimated value exceeds or falls below a predefined threshold, the system adjusts the resource values accordingly. This ensures optimal resource allocation and value management.
2. The system for predicting total allocation of resources in an event, as recited in claim 1 , further comprising: increasing the value of the resource if the total estimated value of the resources is less than the threshold; and decreasing the value of the resource if the total estimated value of the resource is more than the threshold.
This invention relates to a system for predicting and optimizing resource allocation in events, such as conferences, concerts, or other gatherings where resources like seating, staff, or equipment must be allocated efficiently. The system addresses the challenge of accurately estimating resource needs to avoid shortages or excesses, which can lead to inefficiencies or wasted costs. The system dynamically adjusts resource values based on a comparison between the total estimated value of allocated resources and a predefined threshold. If the total estimated value falls below the threshold, the system increases the value of the resource to ensure sufficient allocation. Conversely, if the total estimated value exceeds the threshold, the system decreases the resource value to prevent over-allocation. This adjustment mechanism helps balance resource distribution, ensuring optimal utilization while minimizing waste. The system likely includes a baseline prediction model (as referenced in claim 1) that initially estimates resource requirements. The dynamic adjustment feature refines these estimates in real-time, improving accuracy as more data becomes available. This approach is particularly useful in scenarios where resource demands fluctuate or are difficult to predict in advance. By continuously monitoring and adjusting resource values, the system ensures that allocations align with actual needs, enhancing efficiency and cost-effectiveness.
3. The system for predicting total allocation of resources in an event, as recited in claim 1 , wherein the load corresponds to requests for access rights associated with the resource, an access right facilitating entry to a spatial area associated with the resource.
This invention relates to a system for predicting the total allocation of resources in an event, particularly focusing on managing access rights to spatial areas. The system addresses the challenge of efficiently distributing and predicting resource usage in scenarios where access to physical or virtual spaces is controlled. The system monitors and analyzes load, which corresponds to requests for access rights associated with a resource. An access right in this context facilitates entry to a spatial area linked to the resource, such as a physical venue, a virtual environment, or a restricted zone. The system dynamically assesses the demand for these access rights, enabling optimized resource allocation and preventing overcrowding or underutilization. By predicting the total allocation of resources, the system ensures that access is granted in a controlled manner, enhancing security, efficiency, and user experience. The system may integrate with existing access control mechanisms, such as ticketing systems, authentication protocols, or reservation platforms, to streamline the management of spatial resources. The invention is particularly useful in events where controlled access is critical, such as concerts, conferences, or secure facilities.
4. The system for predicting total allocation of resources in an event, as recited in claim 1 , further comprising determining the future request load, wherein: the future request load includes generating an estimation of the future request load during a time period, and the estimation is generated using one or more interpolation processes.
This invention relates to a system for predicting total resource allocation in an event, addressing the challenge of accurately forecasting resource demands to optimize allocation and prevent shortages or excesses. The system estimates future request loads during a specified time period by applying one or more interpolation processes to historical or real-time data. These interpolation methods analyze patterns in past or current request loads to project future demand, enabling dynamic resource allocation adjustments. The system also includes a baseline prediction mechanism that generates an initial estimate of total resource allocation based on historical data, which is then refined by the interpolation-based future request load estimation. By combining these approaches, the system provides a more accurate and adaptive prediction of resource needs, improving efficiency in resource management for events such as computing workloads, network traffic, or physical resource distribution. The interpolation processes may involve linear, polynomial, or other mathematical techniques to model trends in request loads over time. This predictive capability allows for proactive resource allocation, reducing costs and enhancing system reliability.
5. The system for predicting total allocation of resources in an event, as recited in claim 1 , further comprising determining a future request load for the resource, wherein: the future request load includes generating an estimation of the future request load during a time period, and the estimation is generated using one or more extrapolation processes.
This system predicts the total allocation of resources required for an event by analyzing future request loads. The system determines the expected demand for resources by estimating the future request load during a specified time period. This estimation is generated using one or more extrapolation processes, which project historical or current data trends into the future to forecast demand. The system may also include a method for monitoring resource allocation in real-time, adjusting allocations dynamically based on current usage patterns, and optimizing resource distribution to prevent shortages or excesses. Additionally, the system can identify peak demand periods and allocate resources accordingly to ensure availability. The extrapolation processes may involve statistical models, machine learning algorithms, or other predictive techniques to enhance accuracy. The system aims to improve resource management efficiency, reduce waste, and ensure that resources are available when needed, particularly in scenarios with fluctuating or unpredictable demand.
6. A method for predicting total allocation of resources in an event, the method comprising: accessing one or more data sources storing a plurality of access rights to a resource, wherein each of the access rights is associated with an attribute; generating load data representing a load of user requests, wherein the load of the user requests including requests received from a plurality of user devices requesting that an access right to the resource be allocated to the user device; generating a queue of the user requests based on the load of the user requests received, wherein the queue is generated of users interested in attending the event; predicting probability of allocation of access rights of each of the user requests; identifying current value of the resource associated with the access rights; estimating total value of the resources based on the load of user requests in the queue and the current value of the resources, wherein the total value of resources is sum of all the resources associated each of the access rights; and adjusting the value of the resources if the total estimated value of the resources is greater than or less than a threshold.
This invention relates to resource allocation prediction for events, addressing the challenge of efficiently managing access rights to limited resources while optimizing their value. The method involves accessing data sources containing access rights to a resource, where each right is linked to an attribute. It generates load data representing user request traffic, including requests from multiple devices seeking allocation of access rights. A queue of these requests is formed, representing users interested in attending an event. The system predicts the probability of allocating access rights to each request, identifies the current value of the resource, and estimates the total value of resources based on the queue and current value. The total value is the sum of all resources tied to each access right. If the estimated total value exceeds or falls below a predefined threshold, the system adjusts the resource value accordingly. This approach ensures dynamic resource management, balancing demand and value to optimize allocation decisions. The method dynamically adapts to changing conditions, improving fairness and efficiency in resource distribution for events.
7. The method for predicting total allocation of resources in an event, as recited in claim 6 , further comprising: increasing the value of the resource if the total estimated value of the resources is less than the threshold; and decreasing the value of the resource if the total estimated value of the resource is more than the threshold.
This invention relates to resource allocation prediction in event management, addressing the challenge of optimizing resource distribution to meet predefined thresholds. The method involves estimating the total value of allocated resources for an event and comparing it against a set threshold. If the estimated value falls below the threshold, the system increases the value of one or more resources to meet the requirement. Conversely, if the estimated value exceeds the threshold, the system decreases the value of one or more resources to avoid over-allocation. The adjustment process ensures that resource allocation aligns with the threshold, balancing efficiency and sufficiency. The method may also involve dynamic adjustments based on real-time data or historical trends to refine predictions and allocations. This approach is particularly useful in scenarios where precise resource allocation is critical, such as event planning, project management, or logistics, where deviations from the threshold can lead to inefficiencies or excess costs. The system dynamically recalibrates resource values to maintain optimal allocation, enhancing decision-making and resource utilization.
8. The method for predicting total allocation of resources in an event, as recited in claim 6 , wherein the load corresponds to requests for access rights associated with the resource, an access right facilitating entry to a spatial area associated with the resource.
This invention relates to resource allocation prediction in event management systems, specifically for predicting the total allocation of resources based on access requests. The system addresses the challenge of efficiently managing resource distribution in events where access rights determine entry to spatial areas associated with those resources. The method involves analyzing load data corresponding to requests for access rights, where each access right enables entry to a designated spatial area linked to a resource. By processing these access requests, the system predicts the total resource allocation required for the event, ensuring optimal distribution and preventing shortages or excesses. The prediction model considers historical data, real-time demand patterns, and spatial constraints to generate accurate forecasts. This approach enhances event planning by dynamically adjusting resource allocation based on anticipated access needs, improving efficiency and attendee experience. The system integrates with access control mechanisms to validate and process requests, ensuring seamless resource management throughout the event. The invention is particularly useful in large-scale events where precise resource allocation is critical for smooth operations.
9. The method for predicting total allocation of resources in an event, as recited in claim 6 , further comprising determining the future request load, wherein: the future request load includes generating an estimation of the future request load during a time period, and the estimation is generated using one or more interpolation processes.
This invention relates to resource allocation prediction in event management systems, specifically addressing the challenge of accurately forecasting resource demands to optimize allocation and prevent shortages or excesses. The method involves predicting the total allocation of resources required for an event by first determining the future request load, which is the anticipated demand for resources during a specified time period. The future request load is estimated using one or more interpolation processes, which analyze historical or real-time data to project future demand trends. These interpolation techniques may include linear, polynomial, or spline interpolation, depending on the data characteristics and desired accuracy. The method ensures that resource allocation aligns with expected demand, improving efficiency and reducing waste. Additionally, the system may incorporate dynamic adjustments based on real-time data to refine predictions and enhance allocation accuracy. This approach is particularly useful in event planning, where resource demands can fluctuate unpredictably, and precise forecasting is critical for smooth operations.
10. The method for predicting total allocation of resources in an event, as recited in claim 6 , further comprising determining a future request load for the resource, wherein: the future request load includes generating an estimation of the future request load during a time period, and the estimation is generated using one or more extrapolation processes.
This invention relates to resource allocation prediction in event-driven systems, addressing the challenge of accurately forecasting resource demands to optimize allocation and prevent shortages or over-provisioning. The method predicts total resource allocation by first determining a future request load for the resource. This involves generating an estimation of the future request load during a specified time period. The estimation is derived using one or more extrapolation processes, which analyze historical data or patterns to project future demand. The extrapolation may involve statistical techniques, machine learning models, or other predictive algorithms to forecast load trends. The method ensures efficient resource management by anticipating demand fluctuations, allowing for proactive adjustments in allocation. This approach is particularly useful in dynamic environments where resource needs vary over time, such as cloud computing, event scheduling, or network traffic management. By leveraging extrapolation, the system can adapt to changing conditions and maintain optimal resource utilization.
11. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a processor to perform operations including: accessing one or more data sources storing a plurality of access rights to a resource, wherein each of the access rights is associated with an attribute; generating load data representing a load of user requests, wherein the load of the user requests including requests received from a plurality of user devices requesting that an access right to the resource be allocated to the user device; generating a queue of the user requests based on the load of the user requests received, wherein the queue is generated of users interested in attending the event; predicting probability of allocation of access rights of each of the user requests; identifying current value of the resource associated with the access rights; estimating total value of the resources based on the load of user requests in the queue and the current value of the resources, wherein the total value of resources is sum of all the resources associated each of the access rights; and adjusting the value of the resources if the total estimated value of the resources is greater than or less than a threshold.
This invention relates to a system for managing access rights to a resource, such as an event or service, by dynamically adjusting the value of those rights based on demand. The system addresses the challenge of efficiently allocating limited access rights while maximizing the overall value of the resource. The system operates by accessing one or more data sources that store access rights to a resource, where each right is associated with an attribute. It generates load data representing the volume of user requests for access rights, which are received from multiple user devices. These requests are organized into a queue based on the load, representing users interested in attending an event or accessing the resource. The system then predicts the probability of allocating access rights to each user request and identifies the current value of the resource associated with those rights. It estimates the total value of the resources by summing the values of all access rights in the queue, considering the current value and the load of user requests. If the total estimated value exceeds or falls below a predefined threshold, the system adjusts the value of the resources accordingly. This dynamic adjustment ensures optimal allocation and maximizes the resource's overall value.
12. The non-transitory machine-readable storage for predicting total allocation of resources in an event, as recited in claim 11 , further comprising: increasing the value of the resource if the total estimated value of the resources is less than the threshold; and decreasing the value of the resource if the total estimated value of the resource is more than the threshold.
This invention relates to a system for predicting and optimizing resource allocation in an event, such as a conference, concert, or other large-scale gathering. The problem addressed is the inefficient distribution of resources, such as seating, staff, or equipment, which can lead to underutilization or over-allocation, resulting in wasted costs or poor attendee experience. The system uses a machine-readable storage medium to store data and algorithms for estimating the total value of allocated resources. The system compares this estimated value against a predefined threshold to determine whether adjustments are needed. If the total estimated value is below the threshold, the system increases the value of the resource, which may involve allocating more resources or reallocating existing ones. Conversely, if the total estimated value exceeds the threshold, the system decreases the resource value, either by reducing allocation or reassigning resources elsewhere. The system dynamically adjusts resource allocation in real-time or near-real-time to ensure optimal utilization. This approach helps balance cost efficiency with attendee satisfaction, preventing both shortages and excesses. The invention may also incorporate historical data, predictive analytics, and user feedback to refine future allocations. The goal is to achieve a balanced distribution of resources that aligns with event demands while minimizing waste.
13. The non-transitory machine-readable storage for predicting total allocation of resources in an event, as recited in claim 11 , wherein the load corresponds to requests for access rights associated with the resource, an access right facilitating entry to a spatial area associated with the resource.
This invention relates to resource allocation prediction in event management, specifically for determining total resource requirements based on anticipated access requests. The system predicts the total allocation of resources needed for an event by analyzing load data corresponding to requests for access rights, where an access right grants entry to a spatial area associated with the resource. The prediction model considers historical data, real-time demand patterns, and event-specific factors to estimate the number of access requests and the corresponding resource allocation required. The system dynamically adjusts predictions as new data becomes available, ensuring optimal resource utilization. This approach helps event organizers efficiently allocate resources such as entry points, security personnel, or infrastructure based on predicted demand, reducing over-allocation or shortages. The invention is particularly useful for large-scale events where managing access control and resource distribution is critical. By leveraging machine learning or statistical models, the system provides accurate forecasts to support decision-making in event planning and resource management.
14. The non-transitory machine-readable storage for predicting total allocation of resources in an event, as recited in claim 11 , further comprising determining the future request load, wherein: the future request load includes generating an estimation of the future request load during a time period, and the estimation is generated using one or more interpolation processes.
This invention relates to resource allocation prediction in event management systems, specifically addressing the challenge of accurately forecasting resource demands to optimize allocation. The system predicts total resource allocation for an event by analyzing historical data and current conditions to estimate future request loads. The future request load is determined by generating an estimation of expected requests during a specified time period. This estimation is derived using one or more interpolation processes, which analyze patterns in past request data to project future demand. The interpolation methods may include linear, polynomial, or spline interpolation to ensure accurate predictions based on available data points. By incorporating these techniques, the system enhances resource planning, reducing over-allocation or under-allocation of resources during events. The invention improves efficiency in event management by dynamically adjusting resource distribution in response to predicted demand fluctuations. This approach is particularly useful in scenarios where resource availability is limited or where demand varies significantly over time. The system's ability to interpolate future request loads ensures that resource allocation aligns with expected usage, minimizing waste and ensuring optimal service delivery.
15. The non-transitory machine-readable storage for predicting total allocation of resources in an event, as recited in claim 11 , further comprising determining a future request load for the resource, wherein: the future request load includes generating an estimation of the future request load during a time period, and the estimation is generated using one or more extrapolation processes.
This invention relates to resource allocation prediction in event management systems, specifically for estimating total resource requirements based on future request loads. The system addresses the challenge of accurately forecasting resource needs during events to optimize allocation and prevent shortages or excesses. The invention involves a non-transitory machine-readable storage medium that predicts resource allocation by first determining a future request load for the resource. This load estimation is generated for a specific time period using one or more extrapolation processes, which analyze historical or real-time data to project future demand. The extrapolation processes may include statistical methods, machine learning models, or other predictive algorithms to forecast how resource requests will evolve over time. By integrating these predictive techniques, the system enables dynamic and data-driven resource planning, ensuring efficient allocation during events. The invention also includes determining the total allocation of resources required for the event, which involves calculating the cumulative demand across all predicted requests. This allows event organizers or automated systems to preemptively allocate resources, adjust staffing, or manage inventory to meet anticipated needs. The solution is particularly useful in scenarios where resource demand fluctuates, such as large-scale events, where accurate forecasting is critical for operational efficiency.
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March 29, 2021
March 1, 2022
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